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Comments on "Constructive learning of recurrent neural networks: limitations of recurrent cascade correlation and a simple solution"

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1 Author(s)
S. C. Kremer ; Communication Res. Centre, Ottawa, Ont., Canada

Giles et al. (1995) have proven that Fahlman's recurrent cascade correlation (RCC) architecture is not capable of realizing finite state automata that have state-cycles of length more than two under a constant input signal. This paper extends the conclusions of Giles et al. by showing that there exists a corollary to their original proof which identifies a large second class of automata, that is also unrepresentable by RCC.

Published in:

IEEE Transactions on Neural Networks  (Volume:7 ,  Issue: 4 )